Protocol-centric environments are institutions such as hospitals, step down facilities, nursing and private homes, and the like. A hospital is used herein as an example of a protocol-centric environment. Adverse events that occur in hospitals, such as, for example, hospital-acquired infections, result in patient harm, increased recovery time, unreimbursed healthcare costs, and loss of a hospital's and its staff's capacity to serve. One of the main causes of these events is non-adherence to protocols. As used herein, protocols refer to a series of preferred or prescribed tasks that (1) have been proven to reduce adverse events and (2) effect a desired elimination of activities, practices, or patterns that create harm or inefficiency. Example uses of such protocols are for hand washing, fall prevention, rounding, pain management, sleep improvement, pressure ulcer prevention, and tube management (ventilator, urinary tract, and central line being examples).
As an illustrative example, despite widespread knowledge that proper hand washing reduces pathogen transmission, adherence by visitors of patients under an infection control protocol and even hospital staff can remain low with mean baseline rates of routine compliance across organizations ranging from approximately 50%-81%, with an overall compliance of approximately 40%. While there are many reasons for non-compliance (including a perceived lack of risk, time to wash, missing knowledge of protocol, or associated discomfort from complying with protocol and general inconvenience) improvement in hand sanitization before coming in contact with patients and often upon completing contact, will reduce the spread of bacteria and thus lower the incidence of adverse events, thereby improving the standard of care. It is therefore advantageous to help the providers of healthcare and other persons involved in a patient's care or visitation to comply with protocols.
Many procedures benefit from a higher frequency of protocol compliance. Even relatively low level and treatable infections, such as a urinary tract infection, can escalate to life-threatening conditions including sepsis. Protocols to change tubes, if followed, will reduce the incidence of opportunities leading to infection onset. Other care plans, such as those for ventilators have associated protocols, which if followed, also reduce adverse events. Mortality rates for ventilator associated pneumonia that can be attributed to breaches in patient position and ventilator tube changing protocols, range from approximately 25%-50% and can reach up to 76% in specific settings. Estimates of the costs for one case of ventilator-associated pneumonia have been reported to be $10,000-$16,000 adding an estimated 4-32 additional ventilator days. Harm is therefore inflicted on the patient and a healthcare institution's ability to serve is diminished.
Systems that have been developed to track and analyze activities in a clinical setting have focused primarily on single modality sensing, for example, Radio Frequency Identification (RFID) or infrared (IR) or manual key input or written bed board updates or human observatory monitoring schemas. As an example, one known RFID-based system focuses on identifying human activities in a hospital environment using Hidden Markov Models (HMMs) for supporting context aware applications. While some manufacturing systems may incorporate a combination of RFID and computer vision, the multiple sensors are used to produce a discrete snapshot in time and does not provide contextual information over a period of time.
Typically, RFID sensor systems take the form of location and contact make/break sensing systems for certain protocol adherence. As one example, an institution may specify that staff shall sanitize their hands upon entrance into the patient's room. Since there is little or no mechanism to reason what the staff is doing in the room or context, simple non-nuanced standing procedures are enforced. Sensor systems such as those that are IR or RFID-based determine if staff was in the presence of a hand sanitization station, or if cleansing agents are dispensed. A process defect is alarmed or recorded when staff enter a room and do not sanitize. In other systems, the provider of care wears a device to display they have hand sanitized but partially leave the protocol adherence determination to the patient for warning the care provider.
In non-healthcare domains, such as commercial shopping monitoring, humans in effect become the sensors with such programs as ‘secret shoppers’ and behavioral studies that use shopping patterns to infer consumer propensities to select product preferentially.
However, in such single modality systems a sensor must be associated with the patient, care provider, or apparatus being monitored. Further, such systems do not provide information regarding whether specific behaviors and actions are occurring according to specified temporal-spatial relationships nor do such systems provide in-situ feedback and/or contextually appropriate workflow and/or insightful summary reporting. RFID systems are further limited by their range; typically RFID systems have a tolerance of approximately plus-or-minus 10 feet.
In systems that employ optical sensing, optical tags may be used to identify objects such as specific equipment, patients, care providers, and sundry apparatus. Such systems typically provide optical or other tag information to a video record, may superimpose such information on a display, or may identify the orientation of a plurality of reference points for optical positioning for the purposes of diagnostic imaging or placement of apparatus such as biopsy needles.
The University of Pittsburgh Medical Center has pilot tested a concept of a Smart Room, which includes the integration of speech recognition, ultrasound, and electronic health record data, to support some patient safety and clinical information sharing. However, such system is limited in the number of sensing systems that it employs and uses data from the sensing systems to access appropriate data to post on computer screens in a patient's room. Thus, the system does not provide any contextual meaning to feedback received from the sensors.
Known systems also incorporate a sensor-based system for monitoring caregiver performance focused on avoiding pressure ulcers in patients. However, the sensors such systems typically employ do not monitor position latency, velocities, momentum, or the contextual state of other items that contribute to pressure ulcer formation such as the actions of caregivers and cumulative movements of the patient relative to the desired.
Therefore, it would be desirable to design a system and method for protocol adherence.